论文标题
网络位置和遗传突变的聚类决定了遗传疾病的程式化模型中的慢性性
Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases
论文作者
论文摘要
从高度简化的角度来看，疾病可以看作是遗传易感性和波动环境刺激的相互作用的表型。我们在最小模型中正式化了这种情况，其中网络（表示蜂窝调节）用作输入层（表示环境）和输出层（表示功能表型）之间的接口。疾病的遗传倾向表示某些网络节点的功能丧失。减少但非零的输出表示疾病。这种遗传疾病模型的简单性及其与渗透理论的密切关系使我们能够了解疾病，网络拓扑与受影响网络节点的位置和群集之间的相互作用。我们发现我们的模型产生了两个不同的疾病特征，可以解释为慢性病和急性疾病。我们的模型以其风格化形式提供了有关遗传突变与疾病类型和严重程度之间关系的新观点。
In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.
